Method and system for determining margin requirements

ABSTRACT

The present invention provides for a system and method of applying value-at-risk determination of a financial portfolio to a performance bond requirement and comparing the value-at-risk determination with a traditional scenario-based performance bond requirement.

REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. patent applicationSer. No. 11/766,667 filed Jun. 21, 2007, the content of which isexpressly incorporated herein by reference in its entirety.

TECHNICAL FIELD

The present invention generally relates to a system and method forapplying financial risk data to financial instruments. Moreparticularly, the present invention relates to a system and method forapplying the value-at-risk determination of a financial portfolio to aperformance bond requirement.

BACKGROUND

Most futures commodity exchanges calculate performance bonds using ascenario based system such as the system developed by the ChicagoMercantile Exchange called Standard Portfolio Analysis of Risk™ (SPAN®).Since its implementation, SPAN has become the industry standard forestablishing performance bond or margin requirements associated with afutures portfolio. As such, there has been little in development ofvalue-at-risk determinations for performance bonds. As futures exchangesexpand their product offerings to more complex and exotic products, suchas for example, basis, calendar spread options, and average priceoptions, the limitations of the SPAN system for margin requirementsbecome more apparent.

Additionally, the tiered structure SPAN uses to apply credits maymisrepresent risk. For example, if a customer has long and shortoutright futures positions intended to completely offset his short andlong calendar swaps, SPAN will spread the futures first and the swapssecond effectively producing two sets of spreads with performance bondrequirements on both. The trader would expect the system to spread thelong futures with the short calendar swaps and vice versa which wouldotherwise produce virtually no performance bond requirement. Moreover,the myriad of potential spreads and offsets is difficult if notimpossible to cover while simultaneously margining in true risk termswith the SPAN system because of certain rigidity in the SPAN softwarethat was initially developed for more traditional futures and optionstrading.

Accordingly there is a need in the art for an alternative performancebond or margining system that more accurately determines an exchangecustomer's risk exposure by accounting for all open positions in aportfolio, which accommodates the increasing number of exotic productstraded on the exchange, and better allows for intra and inter commodity,calendar, and exchange positions.

The discussion of the background to the invention herein is included toexplain the context of the invention. This is not to be taken as anadmission that any of the material referred to was published, known, orpart of the common general knowledge as at the priority date of any ofthe claims.

Throughout the description and claims of the specification the word“comprise” and variations thereof, such as “comprising” and “comprises”,is not intended to exclude other additives, components, integers orsteps.

SUMMARY

The present invention addresses a new method and system of establishingand assessing margin requirements. More specifically, the presentinvention provides an improved performance bond requirement or marginingsystem that more accurately accounts for a portfolio's associated riskand overcomes the deficiencies of the SPAN-based system.

The present invention includes a method for accurately determining therisk associated with a portfolio using value-at-risk (“value-at-risk” or“VAR”) methodologies and then using the VAR determination to establish aperformance bond.

The present invention additionally includes a system and method forcomparing the computed VAR-based margin requirement with the traditionalSPAN-based margin requirement associated with a particular portfolio ora subset of a particular portfolio, and communicating the comparison ofthe two margin requirements with an exchange clearing member.

The present invention further includes a method and system for creditingor debiting a margin account with the difference between the VAR-basedmargin requirement and the traditional SPAN-based margin requirement.

An implementation of the present invention is directed to a method ofdetermining margin requirements for a portfolio of positions on productstraded on an exchange, the method comprising: identifying at least oneopen market position within the portfolio of all contracts within theportfolio that are cleared by or on behalf of the exchange; utilizing aVAR protocol to determine a clearing member's risk exposure associatedwith the at least one identified open market position; computing the amargin requirement for said the clearing member; and notifying theclearing member of the computed margin requirement.

An implementation of the present invention is further directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, the method further comprising:receiving a request from a clearing member to determine a marginrequirement based on VAR protocols for a portfolio of positions onproducts traded on an exchange, the portfolio associated with theclearing member.

An implementation of the present invention is still further directed toa method of determining margin requirements for a portfolio of positionson products traded on an exchange, the method further comprisingreceiving a request on behalf of a customer of the clearing member.

Another implementation of the present invention is directed to a methodof determining margin requirements for a portfolio of positions onproducts traded on an exchange, the method further comprising: assessingthe margin requirement to the clearing member in the form of a credit ordebit.

An additional implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, the method further comprising:identifying all open market positions associated with a portfolio.

A further implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, wherein at least one open marketposition comprises at least one off-setting market positions.

Yet another implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, utilizing a VAR protocol based on aparametric model.

An additional implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, utilizing a VAR protocol based on aMonte Carlo simulation.

A further implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, utilizing a VAR protocol based on ahistorical simulation.

And another implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, wherein the margin requirementaccounts for off-setting market positions.

An additional implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, wherein a debit or credit is appliedto a margin account associated with the clearing member.

Another implementation of the present invention is directed to a methodof determining margin requirements for a portfolio of positions onproducts traded on an exchange, wherein a debit or credit is applied toa SPAN-based margin requirement.

A further implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, the method comprising: calculating aSPAN-based margin requirement; comparing the SPAN-based marginrequirement with a margin requirement computed from a risk exposuredetermined utilizing VAR protocols; obtaining a margin requirementvariance; and notifying the clearing member of the margin requirementvariance.

Still another implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, the method further comprisingadjusting a SPAN-based margin requirement by a margin requirementvariance.

An additional implementation of the present invention is directed to amethod of determining margin requirements for a portfolio of positionson products traded on an exchange, the method further comprising:calculating a SPAN-based margin requirement wherein the risk exposuredetermined utilizing VAR protocols is a parameter to the SPAN-basedmargin requirement calculation.

A further implementation of the present invention is directed to asystem for generating a VAR-based performance bond requirement,comprising: a selected position file indicating the open marketpositions associated with a selected trading portfolio; a VAR parametergenerator operative to compute VAR variant files; and a VAR calculationmodule operative to receive the selected position file and the VARvariant files, to compute a VAR-based margin requirement, and generate aVAR-based margin report;

An additional implementation of the present invention is directed to asystem for generating a VAR-based performance bond requirement,comprising a SPAN calculation module operative to receive a selectedposition file and a SPAN parameter file, to compute a SPAN-based marginrequirement, and generate a SPAN-based margin report.

A further implementation of the present invention is directed to asystem for generating a VAR-based performance bond requirement,comprising a comparison module being coupled with a VAR calculationmodule and a SPAN calculation module so as to access a VAR-based marginrequirement and a SPAN-based margin requirement, and being operative tocompare the VAR-based margin requirement with the SPAN-based marginrequirement to compute a revised margin requirement.

Still a further implementation of the present invention is directed to asystem for generating a VAR-based performance bond requirement,comprising a report processor operative to apply the difference betweena VAR-based margin requirement and a SPAN-based margin requirement to anaccount associated with a selected portfolio in the form of a credit ordebit.

Another implementation of the present invention is directed to a systemfor generating a VAR-based performance bond requirement, comprising areport processor operative to apply the difference between a VAR-basedmargin requirement and a SPAN-based margin requirement to a SPAN-basedmargin requirement in the form of a credit or debit.

And yet another implementation of the present invention is directed to asystem for generating a VAR-based performance bond requirement,comprising a VAR parameter archiver being coupled to a VAR parametergenerator and a VAR database, being further operative to categorize VARparameters received from the VAR parameter generator and storing the VARparameters in a VAR database.

As used herein, the term “SPAN based margin requirement,” “SPAN basedperformance bond,” and “SPAN based margin system” refers to marginrequirements or performance bonds, and systems for calculating marginrequirements or performance bonds, that utilize a scenario basedcalculation, such as for example, the CME SPAN system, or to performancebond systems that are based on or derived from a scenario basedperformance bond system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a data flow diagram of a prior-art system for determiningthe VAR measure of an existing trading portfolio.

FIG. 2 depicts a flow chart of a prior-art SPAM-based margining system

FIG. 3 depicts a flow chart of an embodiment of a VAR-based marginingsystem, in accordance with the invention.

FIG. 4 depicts a flow chart of a system for VAR-based margining inaccordance with the invention.

DETAILED DESCRIPTION

Futures exchanges such as the New York Mercantile Exchange, Inc. (NYMEX)provide a marketplace where futures, and options on futures, are traded.Futures is a term used to designate all contracts covering the purchaseand sale of financial instruments or physical commodities for futuredelivery on a commodity futures exchange. A futures contract is alegally binding agreement to buy or sell a commodity at a specifiedprice at a predetermined future time. Each futures contract isstandardized and specifies commodity, quality, quantity, delivery dateand settlement. An option is the right, but not the obligation, to sellor buy the underlying instrument (in this case, a futures contract) at aspecified price within a specified time. In particular, a put option isan option granting the right, but not the obligation, to sell a futurescontract at the stated price prior to the expiration date. In contrast,a call option is an option contract which gives the buyer the right, butnot the obligation, to purchase a specific futures contract at a fixedprice (strike price) within a specified period of time as designated bythe Exchange in its contract specifications. The buyer has the right tobuy the commodity (underlying futures contract) or enter a longposition, i.e. a position in which the trader has bought a futurescontract that does not offset a previously established short position. Acall writer (seller) has the obligation to sell the commodity (or entera short position, i.e. the opposite of a long position) at a fixed price(strike price) during a certain fixed time when assigned to do so by theclearing organization. The term “short” refers to one who has sold afutures contract to establish a market position and who has not yetclosed out this position through an offsetting procedure, i.e. theopposite of long. Generally, an offset refers to taking a second futuresor options on futures position opposite to the initial or openingposition, e.g. selling if one has bought, or buying if one has sold.

A futures exchange clearing organization, sometimes referred to as aclearing house, which may be a division of a futures exchange or anindependent company that works in conjunction with a futures exchange,is responsible for settling trading accounts, clearing trades,collecting and maintaining performance bond funds, regulating deliveryand reporting trading data. Clearing organizations also serve asguarantors, ensuring that the obligations of all trades are met, andthereby protecting buyers and sellers from financial loss that otherwisecould arise in connection with potential default by a counterparty toany futures trade or contract.

Clearing organizations are carefully structured to provide futuresexchanges with solid financial footing. A key component of thisstructure are deposits made to a clearing organization to ensure thattraders meet the contractual obligations of the trades they make. Thesedeposits are known as performance bonds or margin requirements.

Performance bonds or margin requirements are essentially good-faithdeposits which can be used to cover adverse movements in futures prices.The futures exchange, acting through a clearing organization, mustensure that participants have sufficient funds to handle losses. Inorder to protect market participants and the integrity of the market,futures exchanges establish margin requirements at sufficiently highlevels to adequately guard against the risks associated with changingmarket conditions. Futures exchanges establish specific marginrequirements for the exchanges institutional customers, known asclearing members, and separate minimum margin requirements for customersof the clearing members, which may be calculated, for example, at 110%greater for member accounts and 135% greater for all other customers. Asused herein, the term “clearing member” refers to any entity associatedwith a performance bond requirement, including, but not limited totraditional clearing members authorized to hold over night their own ortheir customers' positions on products traded, cleared or settled on anexchange, clearing organizations or houses authorized to clear positionson behalf of an exchange, or individual or institutional entities ormembers of an exchange holding or trading products on an exchange thatare subject to a margin requirement.

The amount required for a performance bond varies according to thevolatility of the product underlying the futures contract; the morevolatility, the larger the performance bond. This is to ensure that thebond will cover maximum losses that a contract would likely incur in asingle day. Performance bonds may be reduced where traders hold oppositepositions in closely correlated markets or spread trades. For example, atrader taking a sell position, also known as a short position, in an S&P500 product while simultaneously taking a buy position, also know as along position, in a NASDAQ 100 product may qualify for a reduced spreadmargin. Similarly, a trader taking a long position in November LightCrude Oil and a short position in November Heating Oil may also qualifyfor a reduced spread margin.

Traders who establish a position, either long, short or somecombination, need only maintain a certain amount of performance bond ormargin in their trading account. The margin required is a percentage ofthe value of the contract, as determined each day, and usually, but notalways, ranges between 5% and 15%. The percentage can range between 0%and 100%; 0% and 90%; 0% and 80%; 0% and 70%; 0% and 60%; 0% and 50%; 0%and 40%; 0% and 30%; 0% and 20%; or 0% and 10%. The percentage variesfor each product according to the product's price and volatility.Futures traders don't exchange the full value of the underlyingcommodity—the “notional value”—of any futures contract. They need onlyensure there is enough margin, or performance bond capital, in theiraccount as they monitor the daily price changes of each contract theyare trading. At the end of each day, and at some exchanges at periodicintervals during the trading day, the futures exchange identifies thecurrent price for each contract or open position held by a trader andthen debits or credits each trader's account according to that price.

Accounts that go under the amount of the deposit required mustimmediately add money to bring the account back up to the minimum,otherwise trading is not permitted on that account. Accounts that areunable to meet the minimum may be closed by the exchange.

Futures exchanges may require that the original margin on all futuresand certain options be deposited by its institutional customers orclearing members on a gross basis for the clearing member's long andshort customers. Accordingly, the exchange may then require thatclearing members obtain initial margins from their customers. Inaddition to initial margin deposits, daily variation margin payments aremade in cash to the exchange clearing organization by clearing memberswho have sustained losses on their futures positions. In turn, gains onfutures positions are remitted to the appropriate clearing member. Forthe clearing member's customers, variation margin payments may berequired by the clearing member if an adverse price movement erodesmargin on deposit below the maintenance margin levels established by theexchange clearing organization.

The margining systems presently used by futures exchanges to calculateperformance bond requirements are based on CME's SPAN system. Marginrequirements established by SPAN are based on the overall risk ofpositions held by a clearing member in both the clearing member's houseand customer accounts. SPAN then determines the overall risk of entireportfolios as calculated through options pricing models. SPAN-basedmargining requirements treat futures and options uniformly. The factorsthat affect option values in options pricing models include futuresprice, volatility, and time to expiration. As factors change, futuresand options either gain or lose value. SPAN uses these factors tocalculate the worst possible scenario and margins an entire portfolio onthis basis. Futures exchanges then require member firms to collect fromtheir customers' margins for open positions based on SPAN.

SPAN is a scenario analysis model that uses fixed software (integratedin clearing member back office books and records systems) and parameterfiles sent to all clearing members on a nightly basis that update thescenarios and data that the software uses. SPAN uses hard coded spreadcredits in the updates for inter and intra commodity spreads todetermine: (1) the overall delta or risk exposure (aggregate position ina specific complex such as Henry Hub Gas recognizing that there areseveral different contracts that use Henry Hub Gas as its underlyingcommodity, such as American and European options, futures, and swaps)and (2) the credit or charge that is attributed to correlations orspreads such as Heat to Gas, Crude to Heat, Calendar spreads etc. Withinthis spread credit methodology SPAN also uses a tiered hierarchy todetermine which products get spread with which other product and inwhich order to create credits or charges added to the risk in aparticular product sector.

The SPAN system, however, has certain deficiencies with regard to intra-and inter-commodity spreads, inter-calendar spreads, and inter-exchangespreads. These deficiencies do not easily accommodate the increasingnumber of complex and relatively exotic products offered on an exchangetrading floor and the associated electronic trading platform.

SPAN Process:

Futures exchanges establish minimum initial and maintenance performancebond levels for products traded through the exchanges facilities,including the trading floor and electronic trading systems. Theseperformance bond requirements are typically based on historical pricevolatilities, current and anticipated market conditions, and otherrelevant information. Performance bond levels vary by product and areadjusted to reflect changes in price volatility and other factors. Bothinitial and maintenance performance bond levels represent the minimumamount of protection against potential losses at which an exchange willallow a clearing member to carry a position or portfolio. Should aclearing member's customer's performance bonds on deposit with theclearing member fall below the maintenance level, many exchanges requirethat the account be pre-margined at the required higher initialperformance bond level. Clearing members may impose more stringentperformance bond requirements than the minimums set by the exchanges. Atthe clearing organization level, clearing members must post at least themaintenance performance bonds for all positions carried by the clearingmember, whether through the clearing members own institutional accountor through its many customer accounts.

In setting performance bond levels, the clearing organization monitorscurrent and historical price movements covering short, intermediate andlonger-term data using statistical and parametric and non-parametricanalysis. The clearing organization, and often the exchanges' directorsor other officers typically set futures maintenance performance bondlevels to cover at least the maximum one-day price move on 95% of thedays during these time periods. The actual performance bond requirementsoften exceed this level. Performance bond requirements for optionsreflect movements in the underlying futures price, volatility, time toexpiration and other risk factors, and adjust automatically each day toreflect the unique and changing risk characteristics of each optionseries. In addition, long options must be paid for in full, andexchanges typically require stringent minimum performance bonds forshort option positions.

Most futures commodity exchanges calculate performance bonds with theSPAN system, which bases performance bond requirements on the overallrisk of the portfolios using parameters determined by CME's Board ofGovernors. Prior to SPAN, performance bond requirements were typicallydetermined using either “strategy-based” or “delta-based” systems. Deltamethodology is based on the measure of the price-change relationshipbetween an option and the underlying futures price and is equal to thechange in premium divided by the change in futures price.

SPAN simulates the effects of changing market conditions and usesstandard options pricing models to determine a portfolio's overall risk.SPAN treats futures and options uniformly. In standard options pricingmodels, three factors most strongly affect options values: theunderlying futures price, volatility (variability of futures price) andtime to expiration. As these factors change, options may gain or losevalue. SPAN constructs scenarios of futures prices and volatilitychanges to simulate what the entire portfolio might reasonably lose overa one day time horizon. The resulting SPAN performance bond requirementcovers this potential loss.

SPAN evaluates overall portfolio risk by calculating the worst probableloss that a portfolio might reasonably incur over a specified timeperiod. SPAN achieves this number by comparing hypothetical gains andlosses that a portfolio would sustain under different market conditions.SPAN typically provides a “Risk Array” analysis of 16 possible scenariosfor a specific portfolio under various conditions. Each scenarioconsists of a “what if” situation in which SPAN assesses the effects ofvariations in price, volatility and time to expiration. Each calculationrepresents a gain or loss based on the possible gains or losses due tochanges in an instrument's price by X and volatility by Y.

SPAN licensed clearing organizations and exchanges individuallydetermine the following SPAN parameters, in order to reflect the riskcoverage desired in any particular market: price scan range, volatilityscan range, intra-commodity spread credit, short option minimum, spotcharge, and inter-commodity spread credit. SPAN then combines financialinstruments within the same underlying group for analysis, and refers tothis grouping as the combined commodity group. For example, futures,options on futures and options on equities on the same stock could allbe grouped under a single combined commodity.

To calculate a performance bond requirement, for each combined commodityin a portfolio, SPAN will: sum the scan risk charges, anyintra-commodity spread and spot charge; apply the offsets for allinter-commodity spread credits within the portfolio; compare the abovesum with any existing short option minimum requirement, and determinethe greater of the two compared as the risk of the combined commodity.

The total margin requirement for a portfolio evaluated with the SPANsystem is the sum of all combined commodities less all credit for riskoffsets between the different combined commodities. United States PatentApplication Pub. No. US 2006/0059607 A1, incorporated herein byreference, describes the specific algorithms and methodologies used in aSPAN-based performance bond system.

SPAN Deficiencies:

The current SPAN-based margin system has certain disadvantages whenapplied to modern exchange product slates available at many exchanges.The SPAN system was not intended to act as a risk management system forthe complex, over-lapping product slates offered on many exchangetrading floors and electronic trading systems. Indeed, there is agrowing need to increase cross margining efficiencies between theexchange floor and the exchanges electronic trading system. Because ofthese certain deficiencies it is possible that the exchange clearingorganization could be under-margined, facing risk beyond its operatingparameters. In other situations, because of the deficiencies of SPAN tohandle modern trading products, the clearing organization could beover-margined.

SPAN is limited in its ability to analyze the risk position for tradingcontracts with both inter-commodity and inter-calendar spreads. Forexample, assume a trader took a long position in both July Light CrudeOil (CLN) and August Brent Crude Oil (CSQ). Concurrently, the sametrader took a short position in August Light Crude Oil (CLQ) andSeptember Brent Crude Oil (CSU). Present SPAN methodology would spreadCLN and CLQ together and also CSQ and CSU together, resulting in twointer-month spreads. The actual risk, however, entails both inter-monthand inter-commodity spreads. While this particular long and shortposition may be accommodated by split allocation, those skilled in theart will appreciate that other more complex relationships would not beaccommodated, for example, a situation in which a trader takes a longposition January Heating Oil (HOF) and February Heating Oil (HOG) whileat the same time taking a short position in March RBOB Gasoline (RBH)and April RBOB Gasoline (RBJ). SPAN methodology would create inter-monthspreads but no inter-commodity spreads. What is needed is acomprehensive margin system that would spread each month of eachcommodity against every month of every commodity.

The ever increasing number of exotic options and trading productsfurther illustrate the inefficiencies of the present SPAN-based marginsystem used in the industry. For example, the SPAN system currently usesthe split allocation method for calendar spread and crack spread optionson a delta basis. This approach effectively utilizes a delta-basedmargin system from the pre-SPAN era. Average price options are even morecumbersome and are considered by SPAN to be a different commodity thantheir associated more traditional options. Moreover, delta-basedmargining of spread options can be inefficient and often inaccurate.

Under SPAN, inter-commodity spread credits between commodities do notreference individual months. The credits are typically determinedaccording to front month relationships (for example, the earlier monthsof a spread relationship). However, customers will get these creditsregardless of which months are spread. For example, if a front monthHeating Oil futures contract is spread against a back-month Crude Oilfutures contract, the credit still applies, although in this instance itis probably unwarranted. A more efficient comprehensive margin systemwould take into account not only which commodities are being spread, butalso which months within that commodity are being spread.

Additionally, futures contracts often have risk reductioncharacteristics when margined across more than one product. For example,Crude Oil may reduce the risk of an offsetting Heating Oil and UnleadedGasoline position. A comprehensive margin system without theinter-calendar and inter-commodity limitations of a SPAN-based marginsystem would allow each position to hedge against the market risk ofeach other position.

VAR as a Risk Measure

Value-at-Risk (VAR) is a method for assessment of market-based financialrisk in the trading of financial instruments which overcomes many of thelimitations of the prior-art performance bond systems. Given a tradingportfolio of financial instruments and a description of the marketvariance characteristics, a VAR analysis statistically determines howmuch of the value of the trading portfolio might be lost over a givenperiod of time with a given level of probability. This determination isoften expressed as the VAR measure. A more complete explanation of theVAR methodology can be found in Return to RiskMetrics: The Evolution ofa Standard, RiskMetrics Group, Inc., April 2004, incorporated herein byreference.

VAR typically measures the market, or price risk of a portfolio offinancial assets—that is, the risk that the market value of theportfolio will decline as a result of changes in interest rates, foreignexchange rates, equity prices, or commodity prices. VAR models aggregatethe several components of price risk into a single quantitative measureof the potential for losses over a specified time horizon, conveying themarket risk of an entire portfolio in one number. Moreover, VAR measuresfocus directly on loss of portfolio value, one of the major reasons forassessing risk.

Though there are many different models used in the art to arrive at avalue-at-risk measure, the common categories of models includeparametric models (including variance-covariance approaches usingequally weighted moving averages and exponentially weighted movingaverages, as well as Monte Carlo simulations for non-linear positions)and historical simulation approaches.

VAR models typically measure market risk by determining how much thevalue of a portfolio could decline over a given period of time with agiven probability as a result of changes in market prices or rates. Forexample, if the given period of time is one day and the givenprobability is 1 percent, the VAR measure would be an estimate of thedecline in the portfolio value that could occur with a 1 percentprobability over the next trading day. Thus, if the VAR measure isaccurate, losses greater than the VAR measure should occur less than 1percent of the time.

Two important components of any VAR model are the length of time overwhich the market risk is to be measured and the confidence level atwhich market risk is measured. The choice of these components greatlyaffects the nature of the VAR model.

The time period used in the definition of value-at-risk, often referredto as the “holding period” is discretionary. VAR models assume that theportfolio's composition does not change over the holding period. Thisassumption argues for the use of short holding periods because thecomposition of active trading portfolios is apt to change frequently.One-day holding periods are typically used, though holding periods couldbe in fractional days or hours, or multiple days, weeks, months, oryears.

Value-at-risk measures are most often expressed as percentilescorresponding to the desired confidence level. For example, an estimateof risk at the 99 percent confidence level is the amount of loss that aportfolio is expected to exceed only 1 percent of the time. It is alsoknown as the 99^(th) percentile VAR measure because the amount is the99^(th) percentile of the distribution of the potential losses of theportfolio. In practice, value-at-risk estimates are typically calculatedfrom the 90^(th) to the 99.9^(th) percentiles, and most commonly fromthe 95^(th) to the 99^(th) percentile range.

Although many approaches may be applied when calculating portfolio VARmodels, including parametric methods, Monte Carlo, and historicalsimulation methods, the use of past data is necessary to estimatepotential changes in the value of the portfolio in the future. Usingpast data makes the assumption that the future will be like or similarto the past. Different VAR models, however, often define the pastdifferently and make different assumptions about how markets will behavein the future.

Two parametric approaches to VAR modeling, the equally weighted movingaverage approach and the exponentially weighted moving average approach,are “variance-covariance” VAR models that assume normality and serialindependence with an absence of non-linear positions such as options.Non-linear positions, however, may be accommodated with known simulationmethods, such as Monte Carlo methods, and used in conjunction withvariance-covariance matrices of the underlying market process or rates.

Variance-covariance approaches to VAR modeling are so named because theycan be derived from the variance-covariance matrix of the relevantunderlying market prices or rates. The variance-covariance matrixcontains information on the volatility and correlation of all marketprices or rates relevant to the portfolio. Knowledge of thevariance-covariance matrix of these variables for a given period of timeimplies knowledge of the variance or standard deviation of the portfolioover the same period.

The dual assumption of normality and serial independence simplifiesvalue-at-risk calculations because all percentiles are assumed to beknown multiples of the standard deviation. Thus, the VAR calculationrequires only an estimate of the standard deviation of the portfolio'schange in value over the holding period. Also, serial independence meansthat the size of a price move on one day will not affect estimates ofprice moves on any other day. Therefore, longer horizon standarddeviations can be obtained by multiplying daily horizon standarddeviations by the square root of the number of days in the longerhorizon. When the assumptions of normality and serial independence aremade together, a single calculation of the portfolio's daily horizonstandard deviation may be used to develop value-at-risk measures for anygiven holding period and any given percentile.

A VAR model may be based on a variance-covariance approach using anequally weighted moving average by calculating a given portfolio'svariance (and thus, standard deviation) using a fixed amount ofhistorical data. The portfolio variance is an equally weighted movingaverage of squared deviations from the mean. The fixed amount ofhistorical data may include a relatively small number of recent days,for example, about seven or less days, about 14, 21, 28, 35, 42, or 49or less days, or greater than 49 days, relying on the assumption thatonly very recent data is relevant to estimating potential movements inportfolio value. Or the fixed amount of historical data may include alarge amount of data accumulated over numerous weeks, months or years,for example about six months or less, six months or more, one year orless, one to five years, or greater than five years. Utilizing largeamounts of data may be preferred to estimate potential movementsaccurately.

The calculation of portfolio standard deviations using an equallyweighted moving average approach is:

${\sigma_{t} = \sqrt{\frac{1}{\left( {k - 1} \right)}{\sum\limits_{s = {t - k}}^{t - 1}\left( {x_{s} - \mu} \right)^{2}}}},$

where σ_(t) denotes the estimated standard deviation of the portfolio atthe beginning of day t. The parameter k specifies the number of daysincluded in the moving average (the “observation period”). The parameterx_(s) specifies the change in portfolio value on day s. And theparameter μ specifies the mean change in portfolio value, which may beassumed to be zero.

Exponentially weighted moving average approaches to variance-covariancebased VAR models emphasize recent historical observations by usingexponentially weighted moving averages of squared deviations. Incontrast to equally weighted approaches, these approaches attachdifferent weights to the past observations contained in the observationperiod. Because the weights decline exponentially, the most recentobservations receive much more weight than earlier observations. Theformula for the portfolio standard deviation under an exponentiallyweighted moving average approach is

$\sigma_{t} = {\sqrt{\left( {1 - \lambda} \right){\sum\limits_{s = {t - k}}^{t - 1}{\lambda^{t - s - 1}\left( {x_{s} - \mu} \right)}^{2}}}.}$

The parameter λ, referred to as the “decay factor,” determines the rateat which the weights on past observations decay as they become moredistant. In theory, for the weights to sum to one, these approachesshould use an infinitely large number of observations k. The parameter μis again preferably assumed to be zero.

Due to the normality and serial independence assumed in parametricapproaches generally and in the variance-covariance approachesexemplified herein, the VAR measure may be expressed as a multiple ofthe standard deviation of a portfolio.

U.S. Pat. Nos. 5,819,237 and 6,085,175, herein incorporated byreference, discuss prior-art systems for determining the VAR measure ofa portfolio. FIG. 1 depicts a data flow diagram of an exemplaryprior-art system for determining the VAR measure of an existing tradingportfolio based off of a variance-covariance method. In such aconventional VAR system, a trading portfolio P of financial instrumentsis decomposed into a series of component asset flows or positions. Thisprocess is often referred to as “shredding,” and produces a set ofpositions that approximates the current value and risk behavior of theportfolio. The positions are then mapped onto a set of specified,benchmark positions made at specified future time intervals from thepresent. The future time intervals are typically know as “tenors” andthe combination of position type (e.g., crude oil, gold, U.S. Dollars,and the like) and a tenor is typically termed a “vertex.” The mapping isuseful in order to provide a representation of the portfolio as astandardized collection of positions. The vertices onto which thepositions are mapped are those also used in a variance-covariance matrixQ of the market values of the benchmark positions. The covariance matrixQ describes the current market characteristics to a reasonable degree ofdetail. The shredding and mapping creates a set p of mapped positionsfrom a portfolio P. These positions are then subjected to arithmeticoperations with covariance matrix Q to produce the VAR measure.

For example, assume that the trading portfolio includes financialinstruments maturing in arbitrary number of days from the present, suchas 22 days. The covariance matrix Q typically includes only vertices forother maturation periods of the given financial instrument, such as at7, 30 and 60 days from the present. In order to reliably determine theVAR measure in a conventional manner, the financial instrument is thenmapped into selected position vertices, for example at either 7 or 30days, or some distribution there between. There are a number of knownmapping and shredding functions available to create the mapped set ofpositions p.

From the mapped positions, the VAR measure of the portfolio isdetermined by taking the square root of the product of the transpose p′of set of mapped asset flows p. The resulting VAR measure specifies howmuch money a trader might lose in the current trading portfolio over agiven interval of time with a given probability.

For example, a financial instrument known as a “currency swap” mayconsist of the promise to pay certain amounts of Deutschemark in returnfor receiving certain amount of U.S. dollars, at certain times.Shredding reduces the currency swap into some set of positions, being,for example, negative in sign for the Deutschemark positions andpositive in sign for the U.S. dollar positions. These shredded positionsare each scheduled to occur at some assigned point in time in thefuture, as determined by the swap contract itself. To measure the marketrisk of the swap, the market risk of a benchmark set of positions isdetermined, for example, for $1 received (or paid) today, in one week,in one month, in 3 months, 6 months, 1 year, and so forth, and similarlyfor 1 DM received (or paid) at the same tenors. The risks are determinedin part by the variances and covariances of all these quantities at theselected tenors, and in part by the amounts of such benchmark (vertex)positions. (Risks are measured only at benchmark tenors becausemeasuring variances and covariances for all possible positions at allpossible arbitrary tenors would be computationally impractical.) Theshredded positions, however, do not necessarily lie exactly upon thevertices where the benchmark risks were measured. Therefore, theshredded positions are “mapped” onto the vertices in amounts that behaveequivalently in terms of risk.

In the currency swap example, the set of shredded asset flows is mappedonto “equivalent-sized” asset flows lying at the vertices. Then the riskof all mapped asset flows is calculated together using the known VARequation, accounting for the risk offsets of low covariance.

Alternatively, and instead of a variance-covariance based VAR model,there are numerous known historical simulation approaches to VAR models.Rather than using a specific quantity of past historical observations tocalculate the portfolio's standard deviation, historical simulationapproaches use the actual percentiles of the observation period asvalue-at-risk measures. For example, for an observation period of 500days, the 99^(th) percentile historical simulation value-at-risk measureis the sixth largest loss observed in the sample of 500 outcomes(because the 1 percent of the sample that should exceed the risk measureequates to five losses.)

In a historical simulation approach, the 95^(th) and 99^(th) percentileVAR measures will not be constant multiples of each other. Moreover,value-at-risk measures for holding periods other than one day will notbe fixed multiples of the one-day value-at-risk measures. Historicalsimulation approaches do not make the assumptions of normality or serialindependence. However, relaxing these assumptions also implies thathistorical simulation approaches do not easily accommodate translationsbetween multiple percentiles and holding periods.

Those skilled in the art will appreciate that there are numerousalternative approaches and models to determine the VAR value of a givenportfolio, including Marginal VAR and Incremental VAR approaches.Marginal VAR determines the amount of risk that a particular positionmay add to a financial portfolio, or in another sense, how the VARmeasure of a portfolio would change if a particular position were boughtor sold. Marginal VAR can be formally defined as the difference betweenthe VAR measure of the total portfolio and the VAR measure of theportfolio without the position of interest. Incremental VAR measures theeffect of buying or selling a relatively small portion of a positionwithin a portfolio on the overall risk of a financial portfolio.Incremental VAR is particularly useful when rebalancing a portfolio,such as selling off a portion of a position without liquidating theentire position.

VAR-Based Margining

To date VAR has not been used to establish performance bond requirementsby an exchange clearing organization. FIG. 2 is a flow chart depicting aprior-art margining system 100 wherein the performance bond requirementis determined using SPAN. The exchange clearing organization 110electronically receives the daily open positions 112 of a particularportfolio P, then using a SPAN-based system 114, the clearingorganization 110 calculates the risk exposure associated with the openpositions and assigns a performance bond or margin requirement 116 basedon the risk exposure. The margin requirement 116 is transmitted to aclearing member 118 who in turn passes the margin requirement to theclearing member's customer 120. After receiving the margin collection122 from its customer 120, the clearing member 118 deposits the clearingmember margin deposit 124 into the clearing member margin account 126with the exchange in order to meet the margin requirement 116.

In an implementation of the present invention, the traditionalSPAN-based margining process is augmented by an additional marginingsystem based on VAR. Referring to FIG. 3, a clearing member makes anelection or a request to include a particular portfolio in an exchange'sVAR-based margining program. Alternatively, a clearing member's customermay elect or request to participate in an exchange's VAR-based marginingprogram by making an election or requesting to include a particularportfolio of at least one or more positions in the VAR program, eitherdirectly to the clearing organization or through the clearing member.All open positions for a given time period, usually the end of aparticular trading session, associated with the selected portfolio areentered into a VAR-based margin system 160 and a SPAN-based marginsystem 114 in order to create a margin report 116 which includes aVAR-based margin requirement, a SPAN-based margin requirement, and acomparison or delta of the VAR-based margin requirement and theSPAN-based margin requirement. In an implementation the VAR-based marginrequirement may be input as an additional variable in the SPAN-basedmargin system.

The margin report may then be communicated to the clearing membertogether with the associated margin requirement. Typically, the clearingmember will then pass along the margin requirement to the clearingmember's customer, collect the necessary fees, and then deposit themargin with the clearing organization.

The ultimate margin requirement that the clearing member is required topost may be based entirely on the SPAN-based margin requirement. In thissituation, the clearing member may use the delta between the SPAN-basedmargin requirement and the VAR-based margin requirement to lower thecash layout the clearing member may require from its customer. Forexample, if SPAN creates a margin requirement of $1000 while theVAR-based margin indicates that $200 more correctly accounts for therisk involved with a selected portfolio, then the clearing member couldcharge $200 dollars to its customer and loan the customer the remaining$800 plus interest to cover the margin requirement. The customerbenefits because it does not have as large a cash requirement and theclearing member profits on the interest charged while having a firmunderstanding of the risk involved with the loan.

Alternatively, the clearing organization could determine the differencebetween the VAR-based margin requirement and the SPAN-based marginrequirement and apply that difference in the form of a credit or debitto the either the SPAN-based margin requirement or the margin accountassociated with the selected portfolio on deposit with the clearingorganization.

FIG. 4 illustrates an exemplary implementation of the invention anddepicts a voluntary VAR-based re-margining process. First the clearingmember selects an account portfolio 201 to participate in VAR. Aposition file 204 is generated indicating all open positions associatedwith the elected account portfolio 201 for a designated time period.Position file 204 is input into a SPAN calculation file 208 togetherwith SPAN parameter files 209 and relevant real time market data 207.SPAN calculation module 208 then uses known SPAN methodologies togenerate SPAN report 218 and SPAN calculation output file 219. SPANreport 218 and SPAN calculation output file 219 input into the clearingmember download 240 which provides the clearing members a performancebond requirement based on SPAM methodologies.

At the same time that selected position file 204 is input into the SPANcalculation module 208, selected position file 204 is also input intoVAR calculation module 206. Current or relevant interest rates 222,volatility inputs 223, and settlement prices 224 are input into VARparameter generator 220, which generates VAR variant files 225 and VARco-variant files 226 according to known VAR parameter methodologies.

VAR variant files 225 and VAR co-variant files 226, together with theselected position file 204, input into VAR calculation module 206wherein VAR-based margin requirements are determined using known VARmethodologies to generate VAR report 214 and VAR calculation output file216. VAR report 214 and VAR calculation file 216 are input into clearingmember download 240.

VAR variant files 225 and VAR co-variant files 226 are also input intoVAR parameter archiver 212, which categorizes variant files 225 andco-variant files 226 by parameters established by the exchange forcataloging into VAR historical database 213. VAR variant files 225 arealso input into the clearing member download 240.

By this process, the clearing member receives, in clearing memberdownload 240, performance bond requirements as reported in SPAN report218 and VAR report 214, together with the supporting calculations forsuch performance bond requirements, as reported in SPAN calculationoutput file 219, and VAR calculation file 216. The clearing member isalso provided with the relevant VAR variant files 225 supporting the VARReport 206. By providing a VAR-based margin report in addition to theSPAN-based report, the exchange provides valuable risk management to theclearing member, which in turn may be offered as a service to theclearing members customers. By way of example, assuming that SPANcreates a margin requirement of $1000 while the VAR-based marginindicates that $200 more correctly accounts for the risk involved with aselected portfolio, the clearing member could charge $200 dollars to itscustomer and loan the customer the remaining $800 plus interest to coverthe margin requirement. The customer benefits because it does not haveas large a cash requirement and the clearing member profits on theinterest charged while having a firm understanding of the risk involvedwith the loan.

The SPAN-VAR difference may also be provided as part of the VoluntaryVAR re-margining process 200 described above. VAR report 214 and VARcalculation output file 216, together with SPAN report 218 and SPANcalculation output file 219, may also input into SPAN VAR differencereport generator 230, which compares and calculates the variance betweenthe two different performance bond requirements and generates SPAN-VARdifference report 231 and SPAN-VAR delta file 232.

SPAN-VAR difference report 231 may be included in the clearing memberdownload 240. SPAN-VAR delta file 232 may also be included in theclearing member download 240 or may be input into clearing member marginreport process 235 which generates an updated margin requirement to theclearing member through updated margin requirement report 236. Theupdated margin requirement accounts for the difference between thetraditional SPAN-based margin requirement and the alternative VAR-basedmargin requirement. This difference could be applied to the clearingmember's margin requirement in the form of either a credit or a debit tothe clearing member's margin account held at the clearing organization.Alternatively, the SPAN-VAR difference could be applied to the outgoingmargin requirement, thereby increasing or decreasing the performancebond required by the clearing organization.

The components described above may be implemented as one or morecomputer software/logic programs/modules stored in a memory or computerstorage device and executable by a computer processor to implement thedisclosed functionality and process. It will be appreciated that thecomponents described above may include a computer system and network.Such a computer system should include a Pentium-class processor, orsuitable equivalent, a hard disk drive with sufficient capacity, amemory with sufficient capacity, and a suitable output device such as aflat panel LCD display. Further the computer should execute anappropriate operating system, such as Microsoft Windows XP, published bythe Microsoft Corporation, located in Redmond, Wash. The computer systemmay include a network interface being of a suitable type for thenetwork, such as an Ethernet or optical based network. The network maybe a public or private network, such as the Internet, an intranet, avirtual private network, or other TCP/IP or non TCP/IP based network, asis known in the art. Further, secure protocols, such as sHTTP orencryption, may be included to protect communication from beingintercepted or modified and to generally authenticate users and ensuresecure operation. It will be appreciated that any suitable computersystem having suitable processing, storage and communications capabilitymay be used with the disclosed embodiments, such as a mainframecomputer, mini-computer, a workstation, a personal computer or apersonal digital assistant. It will be further appreciated that thedisclosed embodiments may be executed on a single computer system or oneor more components may be executed on a computer system which isseparate from one or more computer systems executing the remainingcomponents, and suitably interconnected, such as via a network.

While the disclosed embodiments relate to a computer software programwhich is stored in the memory of a computer and executed by theprocessor(s) of the computer to perform the disclosed functions, it willbe appreciated that one or more of the disclosed components may beimplemented in hardware or a combination of hardware and software, andis implementation dependent.

1. A method comprising: processing a position file indicating openmarket positions associated with a trading portfolio; processing avalue-at-risk variant file; and computing, by a processor, avalue-at-risk-based margin requirement based on the position file andthe value-at-risk variant file.
 2. The method of claim 1, furthercomprising computing a scenario-based margin requirement based on theposition file and a scenario-based parameter file.
 3. The method ofclaim 2, further comprising comparing the value-at-risk-based marginrequirement with the scenario-based margin requirement to compute arevised margin requirement.
 4. The method of claim 2, further comprisingapplying a credit or debit to an account associated with the tradingportfolio based on a difference between the value-at-risk-based marginrequirement and the scenario-based margin.
 5. The method of claim 2,further comprising applying a credit or debit to the scenario-basedmargin requirement based on a difference between the value-at-risk-basedmargin requirement and the scenario-based margin requirement.
 6. Themethod of claim 2, further comprising initiating a loan based on adifference between the value-at-risk-based margin requirement and thescenario-based margin requirement.
 7. The method of claim 1, furthercomprising categorizing and storing value-at-risk parameters in avalue-at-risk database.
 8. A computer readable medium storing computerexecutable instructions that, when executed, cause an apparatus at leastto perform: processing a position file indicating open market positionsassociated with a trading portfolio; processing a value-at-risk variantfile; and computing a value-at-risk-based margin requirement based onthe position file and the value-at-risk variant file.
 9. The computerreadable medium of claim 8, wherein the computer executableinstructions, when executed, causes the apparatus to compute ascenario-based margin requirement based on the position file and ascenario-based parameter file.
 10. The computer readable medium of claim9, wherein the computer executable instructions, when executed, causesthe apparatus to compute a revised margin requirement based on acomparison of the value-at-risk-based margin requirement with thescenario-based margin requirement.
 11. The computer readable medium ofclaim 9, wherein the computer executable instructions, when executed,causes the apparatus to apply a credit or debit to an account associatedwith the trading portfolio based on a difference between thevalue-at-risk-based margin requirement and the scenario-based marginrequirement.
 12. The computer readable medium of claim 9, wherein thecomputer executable instructions, when executed, causes the apparatus toapply a credit or debit to the scenario-based margin requirement basedon a difference between the value-at-risk-based margin requirement andthe scenario-based margin requirement.
 13. The computer readable mediumof claim 9, wherein the computer executable instructions, when executed,causes the apparatus to initiate a loan based on a difference betweenthe value-at-risk-based margin requirement and the scenario-based marginrequirement.
 14. The computer readable medium of claim 8, wherein thecomputer executable instructions, when executed, causes the apparatus tocategorize and store value-at-risk parameters in a value-at-riskdatabase.
 15. An apparatus comprising: a processor; and a memory storingcomputer executable instructions that, when executed by the processor,causes the apparatus at least to perform: processing a position fileindicating open market positions associated with a trading portfolio;processing a value-at-risk variant file; and computing avalue-at-risk-based margin requirement based on the position file andthe value-at-risk variant file.
 16. The apparatus of claim 15, whereinthe computer executable instructions, when executed by the processor,causes the apparatus to compute a scenario-based margin requirementbased on the position file and a scenario-based parameter file.
 17. Theapparatus of claim 16, wherein the computer executable instructions,when executed by the processor, causes the apparatus to compute arevised margin requirement based on a comparison of thevalue-at-risk-based margin requirement with the scenario-based marginrequirement.
 18. The apparatus of claim 16, wherein the computerexecutable instructions, when executed by the processor, causes theapparatus to apply a credit or debit to an account associated with thetrading portfolio based on a difference between the value-at-risk-basedmargin requirement and the scenario-based margin requirement.
 19. Theapparatus of claim 16, wherein the computer executable instructions,when executed by the processor, causes the apparatus to apply a creditor debit to the scenario-based margin requirement based on a differencebetween the value-at-risk-based margin requirement and thescenario-based margin requirement.
 20. The apparatus of claim 15,wherein the computer executable instructions, when executed by theprocessor, causes the apparatus to categorize and store value-at-riskparameters in a value-at-risk database.